The Fan Car

     The idea to reduce Drag and/or improve Downforce on a vehicle using fans at the rear has been around for decades. Specially in the world of motorsports. Examples include Gordon Murray's BT46 and the T50. Here an explanation is made as to why placing a fan behind a car or a container-carrier truck can be used to improve fuel economy.

     The sample car model is of the renowned Ahmed Body. For validation of the numerical simulation, please refer to this post.

     Fig. 1 shows pressure isosurfaces around the car body both with and without fans installed at the rear. It is clear that the pressure difference between rear and front of the car is more when the fans are not available. More pressure difference results in more Drag and a relatively bad fuel economy.

Fig. 1, T-B; Fan disabled, fan enabled

     Fig. 2 shows cross section view of the car. It can be seen that the the boundary layer is re-energized and as a result the flow separation is significantly reduced by adding a fan at the rear. By adding a fan, the vortices are not only moved away from the rear-end of the car but also have smaller size and less intensity, as shown in Fig. 3.

Fig. 2, T-B; Fan disabled, fan enabled. Red arrows represent direction of airflow

Fig. 3, L-R; Fan disabled, fan enabled

Thank you for reading. Please share my work. If you would like to collaborate on a project please reach out.

Aerofoil Kinematics Computational Fluid Dynamics (Update: 01)

This post is about a 2D NACA 0010 aerofoil undergoing various forms of forced kinematics i.e. pure heaving and pitching and a combination of two known as flapping.

Heaving motion is achieved by changing the angle of attack on the aerofoil based on the Eqn. 1.

α_e = arctan[2*π*St_a*cos(2*π*f_h*t)] + α_i               Eqn. 1

The pitching motion is achieved by employing the sliding mesh with the rotational velocity governed by Eqn. 2.

ω = 2*π*f_h*ϑ*cos(2*π*f_h*t)                                 Eqn. 2

w.r.t. Eqn. 1-2 α_e is the effective angle of attack, St_a is Strouhal number (defined as (f_h*h0/U∞)), f_h is the frequency of oscillations, while ω, t and ϑ represent rotational velocity, instantaneous time and pitching angle. h0 is the heaving amplitude and U∞ is the free stream velocity.

The flapping motion is achieved by a combination of the heaving and pitching. In this particular simulation, the aerofoil is in the power extraction mode, meaning the feathering parameter χ is greater in magnitude than 1.0. Feathering parameter is defined by Eqn. 3.

χ = ϑ/arctan(h0*2*π*f_h/U∞)                                  Eqn. 3

The boundary conditions employed for the set of simulations are at Re 50,000, St_a 0.0149, h0 = aerofoil chord length, χ = 1.1 and f_h = 0.5 Hz. The animation of the velocity contours superimposed with streamlines is shown in Fig. 1. The velocity scale ranges from 0 to 7 m/s. Pressure distribution around the aerofoils in various forms of motion, after five complete cycles is shown in Fig. 2.

Fig. 1, Flow animation, fluid flow direction is from left to right

Fig. 2, Fluid flow is from left to right

If you want to collaborate on the research projects related to turbomachinery, aerodynamics, renewable energy, please reach out. Thank you very much for reading.

Computational Fluid Dynamics (CFD) Analysis of a Horizontal Axis Tidal Turbine (Update 01)

     In this post, the results of numerical simulations carried out on a three-blade horizontal-axis tidal turbine blades are made available. These simulations are a part of larger project relating to a horizontal-axis tidal turbine.

 

     The turbine under investigation had a diameter of 4 m. The aero-foils employed include the NACA 4424 (chord length 0.25 m), NACA 4420 (chord length 0.2312 m), NACA 4418 (chord length 0.2126 m), NACA 4417 (chord length 0.1938 m), NACA 4416 (chord length 0.175 m), NACA 4415 (chord length 0.1562 m), NACA 4414 (chord length 0.1376 m), NACA 4413 (chord length 0.1188 m) and the NACA 4412 (chord length 0.1 m) at a distance of 0.4 m, 0.6 m, 0.8 m, 1 m, 1.2 m, 1.4 m, 1.6 m, 1.8 m, 2 m from the blade root, respectively [1].

 

     The numerical simulations were carried out on SolidWorks Flow Simulation Premium software. The software employs κ-ε turbulence model with damping functions, SIMPLE-R (modified) as the numerical algorithm and second order upwind and central approximations as the spatial discretization schemes for the convective fluxes and diffusive terms. The time derivatives are approximated with an implicit first-order Euler scheme. To predict turbulent flows, the Favre-averaged Navier-Stokes equations are used. The software employs a Cartesian mesh which is created using the immersed boundary method.

 

     The simulations were carried out using the Local rotating region(s) (Sliding) technique. The mesh had a total of 589,763 cells. 132,045 cells were at the turbine blade-rotating region boundary. While the process of mesh generation, a mesh control was employed to refine the mesh near the turbine blades and at the boundary of the rotating region and the stationery computational domain. To refine the mesh for the mesh independent test, the curvature level was increased i.e. the mesh in the areas of interest was refined by a factor of 8. As a result, the refined mesh had a total of 916,577 cells. A total of 221,978 were present around the turbine blade. The computational mesh around the turbine blade is shown in Fig. 1. The refined mesh in the areas of high gradients is also clearly visible. The computational domain had dimensions of 2D x 2D x 2.4D, where D is the diameter of the turbine. The dimensions for the computational domain resemble to those in [2].

     Fig. 2 shows computational domain around the turbine blades. In Fig. 2, the curved teal arrow represents the direction of rotation of the turbine. The green arrows represent the respective co-ordinate directions. The brown arrow represents the direction of the force of gravity. The blue arrow represents the direction of the fluid velocity. The circular disc represents the rotating region.

 

Fig. 1, The computational mesh.

    

Fig. 2, The computational domain and the orientation of the boundary conditions.

 

     The simulations were carried out for a total of 5 tip-speed ratios for the turbine ranging from 2 to 10. The fluid; water, velocity was set at 2 m/s. The results are indeed, mesh independent. The mesh independence test was conducted on the design point of the turbine i.e. at the TSR of 6. The plot between the turbine tip-speed ratio; TSR, and the co-efficient of power is shown in Fig. 3. It can be clearly seen from Fig. 3 that the results are in close agreement with the results from [1, 3]. The CFD results from both studies are lower then the BEM, Blade-Element Momentum, results because the three-dimensional effects are not considered while implementing the BEM method.

 

Fig. 3, Turbine efficiency plot.

 

     Fig. 4 shows velocity streamlines colored by velocity magnitude, both of these features are drawn relative to the rotating reference frame, around the turbine blade cross-section at various tip-speed ratios. It can be seen from Fig. 4 that the turbine stalls at TSR of 2 due to a large positive angle of attack. It can also be seen that as the TSR increases, the angle of attack on the blade decreases, it is because of this reason that the power output from the turbine increases.

 

 

Fig. 4, Row 1, L-R; TSR of 2 and 4. Row 2, L-R; TSR of 6 and 8. Row 3, TSR of 10.

 

     Thank you for reading. If you would like to collaborate with research projects, please reach out.

     [1] Binoe E. Abuan, and Robert J. Howell, "The Influence of Unsteady Flow to the Performance of a Horizontal Axis Tidal Turbine," Proceedings of the World Congress on Engineering. London, 2018.

     [2] Ibrahim, I. H., and T. H. New, "A numerical study on the effects of leading-edge modifications upon propeller flow characteristics," Proceedings of Ninth International Symposium on Turbulence and Shear Flow Phenomena. Melbourne, 2015.
     [3] Bahaj, A., Batten, W., & McCann, J. (2007). Experimental verifications of numerical predictions for the hydrodynamic performance of horizontal axis marine current turbines. Renewable Energy, 2479-2490.

Update 01:

     CFD post processing added. One more TSR simulated.

SolidWorks Animation: Transient NREL Phase-VI Wind Turbine CFD Simulation [Validated]

     10 KW wind turbine CFD simulation using Flow Simulation Premium. Design points: 10 m/s wind speed, rotational velocity 7.5 rad/s.

     The rendered volume shows vorticity (curl of the velocity field). It is colored by dynamic pressure. Low pressure in the center of the helix shows very small wind speed.

     Power from the CFD analysis was 9,854.96 W while the experimental power is 10,000 W, a difference of only 1.45 %, that too by using only 693,141 cells in the mesh.

     Do you want me to make a tutorial about the simulation setup with SolidWorks Flow Simulation Premium?

Canal Turbine Concept

It's a concept I am currently working on, so far I gave made a CAD model (renderings attached) of it in SolidWorks and analyzed it using its built in CFD module.

There are many advantages of canal turbines over wind turbines, prominent one's being:

 

Unidirectional flow

Water flows in one direction in a canal so we don't need pitch and yaw control surfaces. That simplifies the design process and reduces weight.

Constant flow rate

We (humans) control water flow rate through canals and it's almost same all year, so we don't have to worry about blade aero foil design to suit variable/abruptly variable flow rate, that makes design process further straight forward.

Large Electricity potential

Canals are 100s of km long, imagine the electricity potential in the canals. You can put these turbines in irrigation canals and it'll power nearby villages and all the irrigation equipment etc.

Higher Power/Discharge Ratio

Water is ~816 times dense (powerful) than air, so for the same discharge (flow) rate we get potentially 816 times more power. Which means more we can make designs that are lighter, smaller and easier to manage and maintain.

Easy maintenance

Fitted less than ~1 m deep inside the canal and can be retracted for maintenance at ground level, making maintenance very easy or better yet, we can maintain them while canals are being cleaned.

Plots for Comparison between Lift and Drag Produced by a Legacy Wing VS a Wing with Tubercles (Humpback Whale Fin's Inspired)

For some reason plots are now showing up in the original post (http://3dimensionaldesigningandmanufacturing.blogspot.com/2015/07/comparison-between-lift-and-drag.html).

Comparison between Lift and Drag Produced by a Legacy Wing VS a Wing with Tubercles (Humpback Whale Fin's Inspired)

* Link for Plots (now showing here for some reason) http://3dimensionaldesigningandmanufacturing.blogspot.com/2015/07/plots-for-comparison-between-lift-and.html

Following data was obtained from the CFD Simulations carried out in SolidWorks Flow Simulation Premium.

Project: Design of a Wing/Blade with Tubercles for Airplanes and/or Turbines

Without Tubercles
Air Speed in Km/h	Lift in N	Drag in N
150	46.307	14.775
140	39.942	12.917
130	33.432	11.057
120	28.807	9.498
110	24.234	7.928
100	20.593	6.625
90	15.836	5.352
80	12.482	4.205
70	9.411	3.243
60	7.272	2.406
50	4.873	1.680
40	3.130	1.082
30	1.763	0.612
20	0.810	0.279
10	0.231	0.072

 

 

With Tubercles
Air Speed in Km/h	Lift in N	Drag in N
150	50.616	11.360
140	48.131	10.008
130	37.190	8.505
120	30.988	7.309
110	24.784	6.079
100	20.892	5.094
90	17.225	4.146
80	13.412	3.287
70	9.955	2.507
60	7.444	1.849
50	4.955	1.286
40	2.991	0.828
30	1.652	0.468
20	0.725	0.212
10	0.214	0.057

 

Comparison between Lift and Drag

Air Speed in Km/h	Percentage Less Drag		Percentage More Lift
150	23.113		8.513
140	22.520		17.014
130	23.080		10.105
120	22.974		7.038
110	23.322		2.219
100	23.109		1.431
90	22.534		8.064
80	21.831		6.934
70	22.695		5.465
60	23.150		2.311
50	23.452		1.655
40	23.475		-7.523
30	23.529		-6.719
20	24.014		-11.72
10	20.833		-7.94

 

It is clear that the wing with tubercles not only produces more lift at a particular velocity but also less drag.

Data for the Wing without Tubercles:

Wing Span: 1.07 m

Chord Length: 0.229 m

Air Velocity: 0-150 Km/h head on

Vertical Pitch: 0 Degree

Gravity Considered

Fluid: Dry Air at STP

Mesh Settings: Coarse (3/8)

Data for the Wing with Tubercles:

Wing Span: 1.067 m

Chord Length Large: 0.229 m

Chord Length Small: 0.203 m

Air Velocity: 0-150 Km/h head on

Vertical Pitch: 0 Degree

Gravity Considered

Fluid: Dry Air at STP

Mesh Settings: Coarse (3/8)

Let's now take a look at visual representation of data.

This Plot Shows Air Velocity VS Drag, Lift by the Wing without Tubercles

This Plot Shows Air Velocity VS Drag, Lift by the Wing with Tubercles

As you can see from above two plots; the wing with tubercles generates more lift and less drag.

This Plot Shows Air Velocity VS Lift Generated by the Wings

The green line represents the Lift generated by the wing with tubercles. It is between two to six percent more at each velocity.

This Plot Shows Air Velocity VS Drag Generated by the Wings

The green line represents the Drag generated by the wing with tubercles. It is around twenty two percent less at each velocity.

This Plot Shows Air velocity VS Lift to Drag Ratio

It is clear from this plot that Lift to Drag ratio of the wing with tubercles is around thirty three percent more for the wing without tubercles at a velocity point.

 

This Plot Shows Air Flow around the Wings at 150 Km/h from the Right Side

This Plot Shows Air Flow around the Wings at 150 Km/h

The Need for Tubercles

In aviation there are four forces at play, Lift which over comes Weight and Thrust which overcomes Drag. For a cruise speed at a particular altitude, three of these forces are almost constant. Our goal is to minimize Thrust, Drag and Weight and maximize Lift, this is because Thrust costs in terms of fuel flow rate and Weight and Drag negatively impacts on the agility of the aircraft. Aerodynamically efficient Wings and/or Blades with "Tubercles" will not only increase Lift and but also decrease Drag. This all means that we will need less Thrust for a cruise speed than before, that results in savings in terms of fuel which will result in healthier environment.

 

Applications:

 

Canal Turbine Concept

It's a concept I am currently working on, so far I gave made a CAD model (renderings attached) of it in SolidWorks and analyzed it using its built in CFD module.

There are many advantages of canal turbines over wind turbines, prominent one's being:

 

Unidirectional flow

Water flows in one direction in a canal so we don't need pitch and yaw control surfaces. That simplifies the design process and reduces weight.

Constant flow rate

We (humans) control water flow rate through canals and it's almost same all year, so we don't have to worry about blade aero foil design to suit variable/abruptly variable flow rate, that makes design process further straight forward.

Large Electricity potential

Canals are 100s of km long, imagine the electricity potential in the canals. You can put these turbines in irrigation canals and it'll power nearby villages and all the irrigation equipment etc.

Higher Power/Discharge Ratio

Water is ~816 times dense (powerful) than air, so for the same discharge (flow) rate we get potentially 816 times more power. Which means more we can make designs that are lighter, smaller and easier to manage and maintain.

Easy maintenance

Fitted less than ~1 m deep inside the canal and can be retracted for maintenance at ground level, making maintenance very easy or better yet, we can maintain them while canals are being cleaned.